1. Field of the Invention
The present invention relates to a method of processing a medical image of a blood vessel, and more particularly, to a method of processing a medical image of a blood vessel that includes applying a Gabor filter to a photographed original blood vessel image in consideration of directions and thicknesses of blood vessels, detecting blood vessel edges in the original blood vessel image and the blood vessel image to which the Gabor filter is applied, fusing the blood vessel image with a blood vessel image in which edges are detected using a neural network sharpening the blood vessel image, and processing the fused blood vessel image using score level fusion so that the blood vessels included in the blood vessel image can be observed more clearly.
2. Discussion of Related Art
In general, a method of obtaining a blood vessel image of a body part such as fingers and the back of the hand has been performed using a radiographic method such as magnetic resonance imaging (MRI), computed tomography (CT), etc.
However, the radiographic methods are problematic because they require a user to take a contrast agent, which makes radiography troublesome and may cause side effects in some users, and it is too expensive to be used for general diagnostic and therapeutic purposes.
In order to solve these problems of radiographic methods, an infrared imaging method using infrared (IR) lighting and an IR camera has been developed as an alternative method for obtaining a blood vessel image.
The infrared imaging method may be used to analyze a blood vessel domain and a non-blood vessel domain from a blood vessel image, since the blood vessel domain is photographed relatively dark, because near-infrared light used to obtain the blood vessel image is absorbed into the hemoglobin included in blood in the blood vessel.
In particular, the infrared imaging method has advantages in that it is less objectionable than MRI or CT, is inexpensive, and has no side effects. Therefore, the infrared imaging method has been widely used in the field of medical imaging to diagnose vessel occlusion caused by arteriosclerosis or to determine whether blood vessels in a joint are correctly joined after incising a body part such as fingers during surgery.
Meanwhile, in order to make an accurate diagnosis and a medical examination in the field of medical imaging using a blood vessel image obtained by the infrared imaging method, a blood vessel domain and a non-blood vessel domain of the obtained blood vessel image have to be clearly observed. Therefore, improving the quality of the blood vessel image using an image sharpening method is essential.
As one example of an attempt to improve the image quality, J. H. KIM, “An Image Merging Method for Two High Dynamic Range Images of Different Exposure,” (Korea Multimedia Society, 2010), discloses that an image is sharpened by obtaining two high dynamic range (HDR) images from an immobilized object at different exposure times, determining a weight value using information such as luminance and chromaticity during combination of the two HDR images, and applying the weight value to the Gaussian function so as to prevent generation of noise that can be caused by a change in the weight value.
However, the method has problems in that it is difficult to predict rotation and movement between the two blood vessel images since the rotation and movement between the two blood vessel images may be caused by a movement of the user, it takes a long processing time to match the blood vessel images, and it is difficult to apply as a method of sharpening a blood vessel image since distortion of a blood vessel domain may be caused by inaccurate matching when the two obtained blood vessel images are obtained from a body part.
Also, as another example of processing a blood vessel image, Z. Shi., W. Yiding, and W. Yunhong, “Extracting Hand Vein Patterns from Low-quality Images: A New Biometric Technique Using Low-cost Devices,” Proceedings of the Fourth International Conference on Image and Graphics, 2007, discloses an attempt to sharpen a blood vessel image by removing noise of an image using a matched filter, a Wiener filter and an average filter.
However, the method has a problem in that an image processed by filtration using a plurality of filters becomes out of focus, and thus a blood vessel and a non-blood vessel may be separated inaccurately during the separation of the blood vessel and the non-blood vessel.
In order to solve these problems, W. Lingyu and L. Graham, “Gray-scale Skeletonization of Thermal Vein Patterns Using the Watershed Algorithm in Vein Pattern Biometrics,” in Proceedings of the International Conference on Computational Intelligence and Security, 2006, proposes a method of extracting a framework of an image by replacing separation of a blood vessel and a non-blood vessel in the image with a watershed algorithm.
However, this method has a problem in that it is difficult to distinguish between two blood vessels when they are adjacent to each other.